With the rapid development of computer network technology and the increasing demand for online education, some online teaching systems have emerged in the market to provide users with, for example, online course or training and English teaching.
For a network teaching system in which a student can choose a teacher independently, the student generally screens and selects desired teachers by inputting keywords. With increase of the number of teachers in a teacher database, the number of teachers in the screened results for a student will also increase. As a result, the student is required to browse a large amount of teacher information before finally determining which teacher to choose. On the other hand, although the student can reduce the number of screened results by using a set of keywords, increasing the number of keywords will inevitably exclude some teachers with certain relevance, which reduces the accuracy of the screened results.
Therefore, how to quickly find a suitable teacher from a large number of teachers is an urgent problem to be solved.